Insider Brief
- Alice & Bob received $3.9 million from ARPA-E to develop fault-tolerant quantum algorithms for designing rare-earth-free permanent magnets.
- The project aims to achieve a 10,000× speed-up over classical simulations using hybrid quantum-classical methods for complex material modeling.
- The three-year effort involves partners including Los Alamos National Laboratory and GE Vernova to advance algorithms, optimization tools, and technoeconomic analysis.
PRESS RELEASE — Alice & Bob, a leader in fault-tolerant quantum computing, has been awarded $3.9 million from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E) Quantum Computing for Computational Chemistry (QC 3) program to develop fault-tolerant quantum algorithms aimed at discovering rare-earth-free permanent magnets – a critical component in electric motors and turbines.
To meet their goal, Alice & Bob will strive to achieve a 10,000-fold speed-up in computing time compared to state-of-the-art classical simulations, enabling realistic material calculations within approximately one day. They will show this speed-up experimentally on Alice & Bob’s fault-tolerant quantum computers, and theoretically with resource estimates.
“Designing high-performance magnets without rare earth elements is one of the hardest problems in material science, as these materials are extremely difficult to simulate with classical computers. A hybrid approach – where classical methods compute environmental parameters and quantum computers simulate highly correlated electronic systems more accurately – could significantly accelerate the discovery of new magnetic materials.”
— said Juliette Peyronnet, U.S General Manager at Alice & Bob.
Alice & Bob will lead the three-year project in collaboration with Los Alamos National Laboratory, GE Vernova’s Advanced Research accelerator, and Professor Emanuel Gull (a visiting Professor at Warsaw University and a Professor at University of Michigan), leading a group that will create classical algorithms that will work in conjunction with Alice & Bob’s quantum algorithms. Los Alamos will develop tensor network tools to optimize quantum circuits, and GE Vernova’s Advanced Research accelerator will perform a technoeconomic analysis of material discovery opportunities enabled by the hybrid algorithm.
“Finding ways to prepare high quality states via tensor network optimization is a critical tool that will help develop fault-tolerant quantum algorithms applied to challenges like rare-earth-free minerals permanent magnets. This team effort converges expertise to leverage quantum computing for an important, practical outcome.”
— Said Marco Cerezo, Los Alamos scientist and Laboratory lead on the project.
“Our team is excited to collaborate with this outstanding technical team and ARPA-E to evaluate how quantum computing could drive forward industrial materials design and discovery,” said Jonathan Owens, Senior Scientist – Computational Materials Physics at GE Vernova’s Advanced Research Center in Niskayuna, NY, U.S.A.
High-performance magnets underpin many technologies central to the global energy transition. Today’s dominant magnet, neodymium-iron-boron (NdFeB), was discovered in the 1980s and relies on rare-earth elements and related processes whose supply chains are geographically concentrated and politically constrained.
Finding alternatives has proven difficult. The magnetic behavior of candidate materials emerges from complex quantum interactions between electrons, making accurate simulation extremely challenging for classical computers. Quantum computers, which directly model quantum systems, could allow researchers to simulate these materials far more efficiently.
If successful, the approach could accelerate the development of cheaper, more sustainable magnets for future energy and industrial technologies. The algorithm developed could also be easily adapted to solve other challenging problems in chemistry and materials science.
